Reading csv file with multiple delimiters in pandas
Introduction This is a memorandum about reading a csv file with read_csv of Python pandas with multiple delimiters. specifying the delimiter using sep (or delimiter) with stuffing these delimiters into “[]” So I’ll try it right away. Details Suppose I have the following csv file (tempo.csv) and I want to read it as separated with some delimiters (the right side of the time has a tab). s1,s2;s3,datetime f1,f2,f3 a,b;c,2020/07/27 03:00 1.2,3.4,5.6 d,e;f,2021/09/28 13:03 2.3,4.5,6.7 g,h;i,2022/11/29 23:45 3.4,5.6,7.8 Here, let’s use the following seven types of delimiters to separate them. “,” “;” “/” ” ” (space) “:” “t”(tab) “.” How to specify the delimiter with sep (or delimiter) is just writing multiple delimiters in [] like this. sep = “[]” And specify engine =’python’ together. Done! By the way, if you read a file without specifying anything, the default delimiter will be “,” Therefore It will be like above. And more；reorder header You may already know by now… Reading a csv file as divided by multiple delimiters, the column header will be shifted and indexed weirdly…. So, replace the header with a list of column names according to the newly generated columns. All done! Reference site. Thank you.https://stackoverflow.com/questions/26551662/import-text-to-pandas-with-multiple-delimitershttps://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html?highlight=delimiter%20csv […]
